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Nika BalomenouView profile

Associate Professor

• Tourism
• Visual Sociology
• Strategic Tourism Planning
• +3 more

Dr. Nika Balomenou is an Associate Professor in Tourism and Visual Sociology at Swansea University's School of Management. She holds leadership roles as co-chair of the Visual Methods in Tourism Research Special Interest Group (Association for Tourism and Leisure Education and Research) and as Programme Director of the MSc International Tourism Management. Previously, she spent 12 years at the University of Hertfordshire, leading the Enterprise and Value Research Group and acting as Research Tutor for the Hertfordshire Business School. Her research focuses on visual methodologies, particularly participant-generated imagery, to empower host communities in tourism contexts. Key areas include strategic tourism planning, national park management, and host-guest interactions. She contributes to prestigious journals like Tourism Management and serves on editorial boards for Destination and Marketing Management and Tourism Planning and Development . Recent work explores tourism's dual impacts through longitudinal studies (e.g., Kavos, Corfu) and innovative visual research methods such as volunteer-employed photography (VEP). Her publications bridge sociological insights with practical tourism planning strategies. Dr. Balomenou supervises PhD candidates in tourism-related topics and teaches modules on strategic tourism planning, experiential design, and research methods. She actively collaborates with industry and policy stakeholders to apply academic findings to real-world challenges.

• Developmental Disorders
• Neuroscience
• Cognitive Science
• +3 more

Adam Naples, PhD, is an Assistant Professor in the Child Study Center at Yale School of Medicine. His research focuses on the neural and cognitive mechanisms underlying developmental disorders, particularly autism. He holds a PhD in Psychology from Yale University and completed postdoctoral training in developmental psychopathology. Naples is affiliated with the McPartland Lab and collaborates on projects within the Autism Biomarkers Consortium for Clinical Trials (ABC-CT). His work integrates EEG, eye-tracking, and PET imaging to study social perception, neural development, and synaptic density in autism. Key research themes include visual attention, social anxiety, and biomarker development for clinical trials. Naples has mentored numerous graduate and undergraduate students and postdoctoral fellows. His lab explores translational approaches to improve early diagnosis and interventions for neurodevelopmental disorders.

Charmaine DeanView profile

Professor

• Biostatistics
• Environmental Science
• Epidemiology
• +7 more

Charmaine Dean is the Vice-President, Research and Professor in the Department of Statistics and Actuarial Science at the University of Waterloo. She holds leadership roles in research administration and academic governance, including previous service as Dean of Science at Western University and Associate Dean at Simon Fraser University. Dr. Dean earned her Ph.D. in Statistics from the University of Waterloo in 1988. Her research focuses on biostatistics, environmental science, and spatio-temporal analysis, with applications to public health, wildfire management, and ecological modeling. Notable contributions include disease mapping, clinical trial design, and statistical methods for analyzing wildfire risk and forest ecology. She has received prestigious awards such as the CRM-SSC Prize, Fellowships from leading statistical societies, and the L’Ordre des Palmes Académiques from France. Her service includes roles on advisory boards for institutions like the Pacific Institute for the Mathematical Sciences and the Banff International Research Station. Dr. Dean’s work bridges academic research and policy, with impactful contributions to environmental and public health policy through interdisciplinary collaborations. Her research group’s activities include developing statistical tools for environmental risk assessment and pandemic response.

• Analytic Number Theory
• Diophantine Geometry
• Arithmetic Statistics
• +3 more

Dante Bonolis is a Phillip Griffiths Assistant Research Professor at Duke University, mentored by Lillian Pierce. His research focuses on Analytic Number Theory, including Diophantine Geometry, Arithmetic Statistics, and applications of trace functions and ℓ-adic cohomology. Prior roles include postdoctoral positions at the University of Basel (2022–2023, mentored by Pierre Le Boudec) and IST Austria (2019–2022, mentored by Tim Browning), and a PhD from ETH Zurich (2014–2019, advised by Emmanuel Kowalski). His teaching includes lectures at Duke (Multivariable Calculus, Matrices and Vector Spaces) and extensive TA experience at ETH Zurich and Basel. Research interests span p-torsion in class groups, harmonic analysis, and polynomial sieve techniques. Recent work includes studies on rational points on algebraic varieties and distributions of Kloosterman sums. No scientific awards explicitly mentioned. Research collaborations include prominent figures like Lillian Pierce, Tim Browning, and Pierre Le Boudec. Teaching spans undergraduate and graduate levels, covering topics like analytic number theory, algebraic geometry, and commutative algebra.

Nicholas OuelletteView profile

Professor

• Complex Systems
• Fluid Dynamics
• Environmental Engineering
• +4 more

Nicholas Ouellette is a Professor of Civil and Environmental Engineering at Stanford University, specializing in complex systems far from equilibrium. His research emphasizes dynamical self-organization across disciplines like fluid dynamics, granular media, and collective animal behavior. He holds a Ph.D. in Physics from Cornell University (2006), an M.S. in Physics (2005), and a B.A. in Physics and Computer Science from Swarthmore College (2002). Prior to Stanford, he was on the faculty at Yale University’s Mechanical Engineering and Materials Science department from 2008-2015. He has received teaching awards at both institutions. His work spans experimental and theoretical studies of turbulence, granular erosion, insect swarms, and urban dynamics. Current research includes sediment transport in turbulent flows, collective behavior in bird flocks, and urban street network analysis. He leads the Environmental Complexity Lab and collaborates on projects involving ocean mixing instrumentation and computational modeling of complex systems. Research interests include turbulent flows in fluids, particle transport dynamics, granular bed erosion mechanics, and quantitative analysis of animal collective motion. Techniques employed range from particle tracking velocimetry to machine learning for free-surface reconstruction. Ouellette’s recent work explores interdisciplinary connections between physics and urban systems, such as pedestrian access optimization in suburban layouts and the interplay of multiple environmental stressors in policy modeling. Notable contributions include studies on midge swarm mechanics, jackdaw flock kinematics, and the application of spectral analysis to energy transfer in turbulence. His lab develops advanced measurement systems for oceanographic studies and applies network theory to environmental and urban systems analysis. Ouellette maintains active collaborations across engineering, biology, and policy domains.

Daeyoung KimView profile

Professor

• Statistics
• Asymmetric Dependence
• Categorical Data Modelling
• +4 more

Daeyoung Kim is a Full Professor in the Department of Mathematics and Statistics at the University of Massachusetts Amherst. He holds a Ph.D. in Statistics from The Pennsylvania State University (2008), and M.S. and B.S. degrees in Statistics from Korea University (2002, 2000). His research focuses on statistical dependence modeling via copulas, likelihood inference in categorical data, mixture modeling, and interdisciplinary applications in food science and environmental engineering. He has authored/co-authored numerous publications, including a book on Direction Dependence in Statistical Modeling . His work spans statistical methodology development and collaborative research in environmental and biomedical sciences. Education: Ph.D. in Statistics, The Pennsylvania State University, 2008 M.S. in Statistics, Korea University, 2002 B.S. in Statistics, Korea University, 2000 Research Interests: Kim’s work emphasizes asymmetric dependence analysis, categorical data modeling, and mixture models. He applies these methods to food science (e.g., lipid metabolism) and environmental challenges (e.g., cyanobacterial bloom modeling). His statistical contributions include copula-based regression and likelihood inference techniques for incomplete data. Collaborative Projects: Kim has contributed to studies on antimicrobial additives’ effects on colonic inflammation, lipid metabolism modulation in disease models, and the role of dietary fats in tumorigenesis. His interdisciplinary collaborations span environmental engineering, nutrition science, and biomedical research. Awards: Noted for award-winning teaching and research excellence, though specific honors are not detailed in the provided text.

David HallidayView profile

Professor

• Computational Neuroscience
• Neural Computing
• Intelligent Systems
• +3 more

Professor David Halliday holds a position at the University of York as a Professor and Chair of the Research Committee. His research focuses on interdisciplinary fields of Computational Neuroscience and Neural Computing, with a particular emphasis on neural networks and neurophysiological signal analysis. He leads the Intelligent Systems and Nano-science Group and maintains an active research profile with over 100 publications. His work integrates theoretical modeling with experimental techniques to investigate topics such as motor control, neural oscillations, and clinical applications of machine learning. David Halliday's academic training includes a BSc and PhD, though specific institutions are not detailed in the provided text. His research interests span computational modeling of neural circuits, development of neuro-inspired algorithms, and application of signal processing techniques to neurological disorders. His homepage at http://www-users.york.ac.uk/~dh20 provides further details, including access to his ResearcherID profile (RID: A-3848-2009). Key research contributions include studies on cortico-muscular coherence in movement disorders, astrocyte-neuron interactions, and fault-tolerant spiking neural networks. His publications demonstrate interdisciplinary collaboration across computational neuroscience, biomedical engineering, and clinical diagnostics. Notably, his work combines experimental neurophysiology with advanced computational methods, such as non-parametric directionality analysis and wavelet-based coherence estimation. Recent studies have addressed clinically relevant topics like gait disturbance in spinal cord injury and biomarker identification in bladder cancer using machine learning approaches.

J. Richard LandisView profile

Professor

• Biostatistics
• Epidemiology
• Clinical Research Informatics
• +6 more

Dr. J. Richard Landis is a Professor of Biostatistics and Statistics at the University of Pennsylvania's Perelman School of Medicine and Wharton School, respectively. As Senior Vice Chair (SVC) of the DBEI Department, he oversees strategic initiatives and serves as a liaison between academic and clinical units. His roles include Director of the Biostatistics Unit at the Center for Clinical Epidemiology and Biostatistics (CCEB), and Director of the Clinical Research Computing Unit (CRCU), supporting translational research infrastructure. He holds advanced degrees from Millersville University (B.S.Ed., 1969), and the University of North Carolina at Chapel Hill (M.S. 1973, Ph.D. 1975). Prior to Penn, he was Professor of Biostatistics at the University of Michigan (1975–1988) and founded Penn State's Center for Biostatistics and Epidemiology (1988–1997). Dr. Landis' research focuses on statistical methodologies for longitudinal and categorical data, with applications to urological, renal, and chronic pain syndromes. He leads NIH-funded Data Coordinating Centers for networks like the MAPP Research Network (2008–2022) and the Chronic Renal Insufficiency Cohort (CRIC) study (2001–2023). His work emphasizes precision medicine, clinical trial design, and translational epidemiology. He has authored over 180 peer-reviewed articles and received prestigious awards, including the Mortimer Spiegelman Gold Medal and the Marvin Zelen Leadership Award. His current projects include the RURAL study (NHLBI) and the HOPE Consortium (NIDDK). Grants & Leadership : NIH-funded DCCs for MAPP, CRIC, and RURAL studies Collaborations : Co-investigator roles in CTSA-Hub cores and multidisciplinary teams Labs/Teams : CRCU, CCEB, and SDCC/SDRC centers

Michael SiegelView profile

Professor

• Firearm violence prevention
• Alcohol policy
• Tobacco control
• +4 more

Michael Siegel is a Professor in the Department of Public Health and Community Medicine at Tufts University School of Medicine. Previously, he spent 26 years at Boston University's School of Public Health. His research focuses on firearm violence, alcohol, tobacco, and racial inequities, with an emphasis on corporate influences on health through advertising and marketing. He also examines structural racism's role in health disparities. Teaching areas include public health advocacy, social and behavioral sciences, health communication, and social marketing. He has served as an expert witness in litigation against tobacco, chemical, and pharmaceutical industries. Education: Master of Public Health (1992), UC Berkeley School of Public Health Doctor of Medicine (1990), Yale University School of Medicine Research Interests: Firearm violence prevention, alcohol and tobacco policy, structural racism analysis, health communication strategies. His work bridges corporate influence analysis and public health advocacy, with recent emphasis on racial inequities' systemic roots. Grants: Funded by 97 Percent Org Inc. (2022-2022) for gun safety policy research Robert Wood Johnson Foundation grant (2021-2021) on firearm policy communication Multiple NIH grants analyzing firearm policy efficacy and racial disparities Teaching: Courses include Public Health Advocacy, Social Marketing, Health Communication Theory, and Strategies for Public Health Advocacy. Recent teaching spans 2022–2025 with focus on practical public health interventions and advocacy.

Andreas AlfonsView profile

Associate Professor

• Statistics
• Machine Learning
• Psychometrics
• +3 more

Dr. Andreas Alfons is an Associate Professor in the Department of Econometrics at Erasmus School of Economics, Erasmus University Rotterdam. His research focuses on robust statistical methods, machine learning, psychometrics, and software development for high-dimensional data. He leads the NWO Vidi project on robust analysis of rating-scale data and contributes to the interdisciplinary project on digital decision support. He is an editor for the Journal of Statistical Software and Journal of Data Science, Statistics, and Visualization. His research interests include robust statistical learning, high-dimensional data analysis, and open science practices. Key contributions include R packages like robmed , robustHD , and simFrame . Recent work addresses careless responding in surveys and robust mediation analysis. Publications span journals such as Computational Statistics & Data Analysis , Econometrics and Statistics , and Journal of Statistical Software . His work emphasizes reproducibility and software tools for statistical analysis.

Thomas WahlView profile

Associate Professor

• Coastal Flood Risk
• Sea Level Rise
• Storm Surges
• +7 more

Thomas Wahl is an Associate Professor in the Department of Civil, Environmental, and Construction Engineering at the University of Central Florida (UCF), within the College of Engineering and Computer Science. He leads the Coastal Risks and Engineering (CoRE) Lab and is a key member of the UCF Coastal Systems Faculty Cluster, focusing on climate-driven coastal hazards. Education: Diploma in Civil Engineering, University of Siegen, Germany Ph.D. in Civil Engineering, University of Siegen, Germany (2012) His research centers on coastal flood risk , sea level rise , storm surges , and compound climate extremes . He investigates how multiple hazards—such as high tides, storm surges, rainfall, and river discharge—interact to create extreme flooding, especially under climate change. His work aims to develop actionable science for coastal resilience and adaptation planning. The recent publications (2022–2023) highlight a strong trend in analyzing compound flooding, sea-level extremes, and their socio-environmental impacts across the U.S., China, Europe, and global coasts. His research integrates observational data, climate modeling, and multivariate statistics to assess current and future risks. Scientific Awards: Walter L. Huber Civil Engineering Research Prize, ASCE (2023) NSF CAREER Award (2022) Early Career Scientist Medal, IAPSO (2021) Outstanding Early Career Scientist Award, EGU (2018) NASA Early Career Investigator Award (2018) Wahl advises graduate students and leads a dynamic research group in the Coastal Risks and Engineering (CoRE) Lab , which studies extreme sea levels, compound events, and coastal risk modeling. His research is supported by major grants from NSF, NASA, and other federal agencies. He has collaborated extensively with institutions including the University of South Florida, University of Southampton, and international climate research centers.

• Artificial Intelligence in Radiology
• Machine Learning
• Health Informatics
• +2 more

Dr. Axel W. E. Wismüller is a Professor of Radiology and Biomedical Engineering at the University of Rochester Medical Center . As Director of the AI Radiology Laboratory , he uniquely combines clinical practice in cardiothoracic/body imaging with pioneering research in Artificial Intelligence (AI) for medical imaging . Holding MD, MSc (Physics), and PhD (Electrical Engineering) degrees from German institutions, he maintains dual US and German medical licenses and board certifications. Ludwig-Maximilians-Universitaet München (1990-1996) Technical University of Munich (MD 1992, PhD 2006) Ludwig Maximilians University Munich (Residency 1997-2005) His research focuses on machine learning and network connectivity analysis in neuroimaging, particularly for HIV-associated neurocognitive disorders and multiple sclerosis . He invented the XOM algorithm (patented in US/EU) and developed AI systems for chest radiograph analysis , breast cancer imaging , and osteoporosis diagnostics . His work on large-scale Granger causality has transformed brain network analysis methodology. Scientific awards include SPIE Senior Membership (2016), NIH/NIDA R01 funding (2012-2015), and NYSTAR public-private partnerships . Supervising over 30 PhD/MSc students across engineering, computer science, and medicine , he bridges clinical and computational disciplines through active roles in ACR, RSNA, and SPIE .

Eldad DavidovView profile

Professor

• Quantitative Methods
• Empirical Social Research
• Cross-Cultural Comparisons
• +5 more

Eldad Davidov is a Professor of Methods of Comparative Cross-National Social Research at the Institute of Sociology and Social Psychology, University of Cologne. He previously held professorships at the University of Zurich (2009-2016) and served as President of the European Survey Research Association (ESRA, 2015-2017). His research focuses on quantitative methods, cross-cultural comparisons, structural equation modeling, and attitudes/values analysis. Davidov has held visiting professorships at Mannheim and Cologne, and his work emphasizes methodological rigor in social research. PhD: Social Sciences, University of Giessen (2004) MA: Economics, Tel Aviv University (1996) BA: Economics, Tel Aviv University (1995) His research interests include: Measurement equivalence in cross-national surveys Value orientations and their societal implications Immigration attitudes and prejudice mechanisms Longitudinal survey data analysis Key publication themes involve analyzing immigration opposition, human values measurement, and methodological advancements in cross-cultural research. His work bridges theory and practice, contributing to the European Social Survey and policy-relevant studies on integration policies. Davidov is affiliated with the Center for Social and Economic Behavior (C-SEB) and contributes to the ECONtribute Cluster of Excellence. His research addresses societal challenges through interdisciplinary collaboration, emphasizing evidence-based approaches to public policy.

Youngsoo ShinView profile

Assistant Professor

• Human-Centered Artificial Intelligence
• User Experience (UX) Design
• Cognitive Science
• +5 more

Dr. Youngsoo Shin is an Assistant Professor at the Seidenberg School of Computer Science and Information Systems at Pace University. His academic foundation spans psychology, integrated design, cognitive science, and human behavior, with degrees from Yonsei University and Cornell University. PhD in Human Behavior & Design, Cornell University (2023) MS in Cognitive Science & Engineering, Yonsei University (2015) BA in Psychology and BS in Human Environment & Design, Yonsei University (2013) Dr. Shin's research focuses on human-centered AI , developing adaptive systems to enhance user experience and AI performance. His work examines emotional, social, and cultural impacts of human-AI interactions, with an emphasis on ethical alignment and prosocial behavior design . Recent publications highlight trends in hyper-personalized recommender systems , behavioral intervention technologies , and UX design guidelines for time management systems. Dr. Shin has taught courses such as Human-AI Interaction, Cognitive Science & Technology, and Product Development Project, reflecting his interdisciplinary expertise in user experience , data science , and cognitive modeling .

Violaine Saint-AndréView profile

Researcher

• Computational Biology
• Immunology
• Epigenetics
• +3 more

Violaine Saint-André is a Researcher at the Institut Pasteur's Bioinformatics and Biostatistics Hub, where she leads computational biology research focused on immune response determinants through the Milieu Intérieur project. She holds a PhD in Molecular Biology/Genetics from Université Paris VI and an MSc in Bioinformatics from Université Paris VII. Her research investigates transcriptional regulatory networks, epigenetic mechanisms, and multivariate analysis of immune variability. Key interests include: Gene expression regulation and epigenetic memory of environmental exposures Determinants of human immune response heterogeneity Computational methods for multi-omics data integration Impact of smoking on long-term immune adaptation Her publications demonstrate strong focus on immunology and computational biology, with recent work uncovering smoking's persistent epigenetic effects on immunity and cytokine regulation. Research frequently involves high-dimensional data analysis across tuberculosis, COVID-19, and HIV contexts. She contributes significantly to academic training through courses at Institut Pasteur, Centrale-Supelec, and École Centrale de Nantes, covering ChIP-seq analysis, multivariate statistics, and health applications of AI. Actively participates in conference organization and student evaluation committees.